Internet finance has permeated into myriad households, bringing about lifestyle convenience alongside potential risks. Presently, internet finance enterprises are progressively adopting machine ...learning and other artificial intelligence methods for risk alertness. What is the current status of the application of various machine learning models and algorithms across different institutions? Is there an optimal machine learning algorithm suited for the majority of internet finance platforms and application scenarios? Scholars have embarked on a series of studies addressing these questions; however, the focus predominantly lies in comparing different algorithms within specific platforms and contexts, lacking a comprehensive discourse and summary on the utilization of machine learning in this domain. Thus, based on the data from Web of Science and Scopus databases, this paper conducts a systematic literature review on all aspects of machine learning in internet finance risk in recent years, based on publications trends, geographical distribution, literature focus, machine learning models and algorithms, and evaluations. The research reveals that machine learning, as a nascent technology, whether through basic algorithms or intricate algorithmic combinations, has made significant strides compared to traditional credit scoring methods in predicting accuracy, time efficiency, and robustness in internet finance risk management. Nonetheless, there exist noticeable disparities among different algorithms, and factors such as model structure, sample data, and parameter settings also influence prediction accuracy, although generally, updated algorithms tend to achieve higher accuracy. Consequently, there is no one-size-fits-all approach applicable to all platforms; each platform should enhance its machine learning models and algorithms based on its unique characteristics, data, and the development of AI technology, starting from key evaluation indicators to mitigate internet finance risks.
Internet finance has permeated into myriad households, bringing about lifestyle convenience alongside potential risks. Presently, internet finance enterprises are progressively adopting machine ...learning and other artificial intelligence methods for risk alertness. What is the current status of the application of various machine learning models and algorithms across different institutions? Is there an optimal machine learning algorithm suited for the majority of internet finance platforms and application scenarios? Scholars have embarked on a series of studies addressing these questions; however, the focus predominantly lies in comparing different algorithms within specific platforms and contexts, lacking a comprehensive discourse and summary on the utilization of machine learning in this domain. Thus, based on the data from Web of Science and Scopus databases, this paper conducts a systematic literature review on all aspects of machine learning in internet finance risk in recent years, based on publications trends, geographical distribution, literature focus, machine learning models and algorithms, and evaluations. The research reveals that machine learning, as a nascent technology, whether through basic algorithms or intricate algorithmic combinations, has made significant strides compared to traditional credit scoring methods in predicting accuracy, time efficiency, and robustness in internet finance risk management. Nonetheless, there exist noticeable disparities among different algorithms, and factors such as model structure, sample data, and parameter settings also influence prediction accuracy, although generally, updated algorithms tend to achieve higher accuracy. Consequently, there is no one-size-fits-all approach applicable to all platforms; each platform should enhance its machine learning models and algorithms based on its unique characteristics, data, and the development of AI technology, starting from key evaluation indicators to mitigate internet finance risks.
Livestock have undergone domestication and consequently strong selective pressure on genes or genomic regions that control desirable traits. To identify selection signatures in the genome of Chinese ...Rongchang pigs, we generated a total of about 170 Gb of DNA sequence data with about 6.4-fold coverage for each of six female individuals. By combining these data with the publically available genome data of 10 Asian wild boars,we identified 449 protein-coding genes with selection signatures in Rongchang pigs, which are mainly involved in growth and hormone binding, nervous system development, and drug metabolism. The accelerated evolution of these genes may contribute to the dramatic phenotypic differences between Rongchang pigs and Chinese wild boars. This study illustrated how domestication and subsequent artificial selection have shaped patterns of genetic variation in Rongchang pigs and provides valuable genetic resources that can enhance the use of pigs in agricultural production and biomedical studies.
In this study, the multi-objective optimization and decision-making for optimal positions of actuators and consensus adaptive dynamic programming (CADP) are investigated to mitigate the vibration of ...large flexible space structures (LFSS). The optimization of the actuator positions maintains a balance between maximizing actuation efficiency and maximizing input voltage decoupling. Meanwhile, the CADP control method accelerates the attenuation of vibration when agents collaborate in the designed communication topology network. First, the electromechanical coupled dynamic model of the LFSS is built by the finite element method. Subsequently, the multi-objective optimization criteria are proposed, which maximize the actuation efficiency and decoupling of control inputs. Moreover, the multi-objective optimization and decision-making, which is based on the non-dominated sorting differential evolutionary algorithm (NSDE) and technique for order preference by similarity to ideal solution (TOPSIS), respectively, are performed to rapidly find the optimal position of actuators. In addition, the CADP control algorithm is designed and its stability is proven. Finally, for harmonic excitation under multi-frequency superposition, simulation comparisons based on the CADP and adaptive dynamic programming (ADP) are performed. Simulation results verify the effectiveness of the proposed optimization criterion of actuators and the CADP algorithm for vibration mitigation of LFSS.
Current tools for targeted RNA editing rely on the delivery of exogenous proteins or chemically modified guide RNAs, which may lead to aberrant effector activity, delivery barrier or immunogenicity. ...Here, we present an approach, called leveraging endogenous ADAR for programmable editing of RNA (LEAPER), that employs short engineered ADAR-recruiting RNAs (arRNAs) to recruit native ADAR1 or ADAR2 enzymes to change a specific adenosine to inosine. We show that arRNA, delivered by a plasmid or viral vector or as a synthetic oligonucleotide, achieves editing efficiencies of up to 80%. LEAPER is highly specific, with rare global off-targets and limited editing of non-target adenosines in the target region. It is active in a broad spectrum of cell types, including multiple human primary cell types, and can restore α-L-iduronidase catalytic activity in Hurler syndrome patient-derived primary fibroblasts without evoking innate immune responses. As a single-molecule system, LEAPER enables precise, efficient RNA editing with broad applicability for therapy and basic research.
•Effectiveness of anticorruption is attested from the view of executive incentive.•In short run, anticorruption decreases the positive effect of pay on performance.•In short run, anticorruption ...escalates the pay-performance sensitivity.•Short-run reduction in executive incentive is more salient in state-owned firms.•Anticorruption should be a long-term strategy.
This paper investigates how anticorruption measures affect corporate governance, especially the executive incentive mechanism. The results of empirical tests show that in the short term, alleviating corruption does not enhance executives incentive, however, it significantly escalates pay-performance sensitivity. It is also found reductions in executive incentive in state-owned companies are more salient than in non-state-owned companies. The suggestion is that anticorruption measures at firm level should be a long-term strategy and focus on state-owned companies. It provides a new perspective for understanding how anticorruption affects firm behavior and performance and for the literature on executive incentives with political intervention.
Diabetes mellitus, characterized by abnormally high blood glucose levels, gives rise to impaired bone remodeling. In response to high glucose (HG), the attenuated osteogenic differentiation capacity ...of human periodontal ligament stem cells (hPDLSCs) is associated with the loss of alveolar bone. Recently, DNA methylation was reported to affect osteogenic differentiation of stem cells in pathological states. However, the intrinsic mechanism linking DNA methylation to osteogenic differentiation ability in the presence of HG is still unclear. In this study, we found that diabetic rats with increased DNA methylation levels in periodontal ligaments exhibited reduced bone mass and density. In vitro application of 5-aza-2'-deoxycytidine (5-aza-dC), a DNA methyltransferase inhibitor, to decrease DNA methylation levels in hPDLSCs, rescued the osteogenic differentiation capacity of hPDLSCs under HG conditions. Moreover, we demonstrated that the canonical Wnt signaling pathway was activated during this process and, under HG circumstances, the 5-aza-dC-rescued osteogenic differentiation capacity was blocked by Dickkopf-1, an effective antagonist of the canonical Wnt signaling pathway. Taken together, these results demonstrate for the first time that suppression of DNA methylation is able to facilitate the osteogenic differentiation capacity of hPDLSCs exposed to HG, through activation of the canonical Wnt signaling pathway.
As the emerging variants of SARS-CoV-2 continue to drive the worldwide pandemic, there is a constant demand for vaccines that offer more effective and broad-spectrum protection. Here, we report a ...circular RNA (circRNA) vaccine that elicited potent neutralizing antibodies and T cell responses by expressing the trimeric RBD of the spike protein, providing robust protection against SARS-CoV-2 in both mice and rhesus macaques. Notably, the circRNA vaccine enabled higher and more durable antigen production than the 1mΨ-modified mRNA vaccine and elicited a higher proportion of neutralizing antibodies and distinct Th1-skewed immune responses. Importantly, we found that the circRNARBD-Omicron vaccine induced effective neutralizing antibodies against the Omicron but not the Delta variant. In contrast, the circRNARBD-Delta vaccine protected against both Delta and Omicron or functioned as a booster after two doses of either native- or Delta-specific vaccination, making it a favorable choice against the current variants of concern (VOCs) of SARS-CoV-2.
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•Highly stable circRNA vaccines induce potent humoral and cellular immune responses•CircRNA vaccines elicit a high proportion of neutralizing antibodies•CircRNA vaccines enable effective protection against SARS-CoV-2 in mice and monkeys•CircRNARBD-Delta vaccine provides broad-spectrum protection against SARS-CoV-2 VOCs
A circular RNA (circRNA) vaccine that encodes the trimeric RBD antigens of SARS-CoV-2 spike provides protection and memory boosting against SARS-CoV-2 variants of concern, in mice and rhesus macaques.
Current methods for programmed RNA editing using endogenous ADAR enzymes and engineered ADAR-recruiting RNAs (arRNAs) suffer from low efficiency and bystander off-target editing. Here, we describe ...LEAPER 2.0, an updated version of LEAPER that uses covalently closed circular arRNAs, termed circ-arRNAs. We demonstrate on average ~3.1-fold higher editing efficiency than their linear counterparts when expressed in cells or delivered as in vitro-transcribed circular RNA oligonucleotides. To lower off-target editing we deleted pairings of uridines with off-target adenosines, which almost completely eliminated bystander off-target adenosine editing. Engineered circ-arRNAs enhanced the efficiency and fidelity of editing endogenous CTNNB1 and mutant TP53 transcripts in cell culture. Delivery of circ-arRNAs using adeno-associated virus in a mouse model of Hurler syndrome corrected the pathogenic point mutation and restored α-L-iduronidase catalytic activity, lowering glycosaminoglycan accumulation in the liver. LEAPER 2.0 provides a new design of arRNA that enables more precise, efficient RNA editing with broad applicability for therapy and basic research.
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